A mathematical model of chikungunya dynamics and control: the major epidemic on Réunion Island

• Published in: PloS one Vol. 8; no. 3; p. e57448
• Main Authors: Yakob, Laith, Clements, Archie C A
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 06.03.2013; Public Library of Science (PLoS)
• Subjects: Alphavirus Infections - epidemiology; Alphavirus Infections - prevention & control; Alphavirus Infections - transmission; Animals; Aquatic insects; Australia - epidemiology; Biological effects; Biology; Chikungunya Fever; Chikungunya virus; Communicable Disease Control; Computer Science; Computer simulation; Culicidae; Disease control; Disease transmission; Epidemics; Epidemiology; Female; Fever; Humans; Infections; Infectious diseases; Insect Vectors; Insecticides; Islands; Latent period; Malaria; Male; Mathematical models; Medicine; Models, Biological; Monte Carlo simulation; Mosquitoes; Ordinary differential equations; Outbreaks; Pathogens; Population; Retrospective Studies; Sensitivity analysis; Surveillance; Travellers; Tropical diseases; Vector-borne diseases; Vectors (Biology); Viruses; Zoonoses; Australia; Europe
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0057448

Chikungunya is a re-emerging arboviral disease transmitted by Aedes spp. mosquitoes. Although principally endemic to Africa and Asia, recent outbreaks have occurred in Europe following introductions by returning travellers. A particularly large outbreak occurred on Réunion Island in 2006, the published data from which forms the basis of the current study. A simple, deterministic mathematical model of the transmission of the virus between humans and mosquitoes was constructed and parameterised with the up-to-date literature on infection biology. The model is fitted to the large Réunion epidemic, resulting in an estimate of 4.1 for the type reproduction number of chikungunya. Although simplistic, the model provided a close approximation of both the peak incidence of the outbreak and the final epidemic size. Sensitivity analysis using Monte Carlo simulation demonstrated the strong influence that both the latent period of infection in humans and the pre-patent period have on these two epidemiological outcomes. We show why separating these variables, which are epidemiologically distinct in chikungunya infections, is not only necessary for accurate model fitting but also important in informing control.